_base_ = [
    "../_base_/models/mask_rcnn_r50_fpn.py",
    "../_base_/datasets/coco_instance.py",
    "../_base_/schedules/schedule_1x.py",
    "../_base_/default_runtime.py",
]
norm_cfg = dict(type="GN", num_groups=32, requires_grad=True)
model = dict(
    pretrained=None,
    backbone=dict(frozen_stages=-1, zero_init_residual=False, norm_cfg=norm_cfg),
    neck=dict(norm_cfg=norm_cfg),
    roi_head=dict(
        bbox_head=dict(
            type="Shared4Conv1FCBBoxHead", conv_out_channels=256, norm_cfg=norm_cfg
        ),
        mask_head=dict(norm_cfg=norm_cfg),
    ),
)
# optimizer
optimizer = dict(paramwise_cfg=dict(norm_decay_mult=0))
optimizer_config = dict(_delete_=True, grad_clip=None)
# learning policy
lr_config = dict(warmup_ratio=0.1, step=[65, 71])
runner = dict(type="EpochBasedRunner", max_epochs=73)
